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Data transfer via noisy neurons.

One of the central puzzles of neurophysiology concerns how the dense web of neurons in the brain encodes sensory information carried from eyes and ears to the brain's central processing regions. Researchers have monitored this neural traffic by measuring the rate at which neurons generate voltage pulses, or spikes, but have so far failed to determine precisely how these spikes convey information.

Now a group of physicists had identified a simple physical mechanism that appears to reproduce key features of the timing of neutral pulses. Their model suggests that noise -- random fluctuations superimposed on signals carried from sensory organs to the brain's processing centers -- plays a crucial role in the transmission of sensory information. Andre Longtin of the Los Alamos (N.M.) National Laboratory and his co-workers describe their mechanism in the July 29 PHYSICAL REVIEW LETTERS.

To monitor the response of a single neuron to a smoothly varying, periodic signal, neurophysiologists typically measure the time intervals between successive spikes. When plotted in the form of a histogram showing how often different time intervals come up, the data typically display a characteristic pattern, with the largest number of recorded time intervals corresponding to the period of the incoming signal.

Longtin and his collaborators investigated -- both experimentally (in the form of an electronic circuit) and theoretically -- the behavior of a system that switches back and forth between two states in response to a noisy, periodic signal. With only noise present, the system randomly switches from one state to the other. However, as the intensity of the smooth, periodic component increases, the switching times start following the signal's oscillations, even though the signal by itself isn't strong enough to force the system to switch from one state to the other. This phenomenon is known as stochastic resonance (SN: 2/23/91, p.127). Simply by adjusting either the noise level or the stimulus intensity -- and by measuring and plotting the time intervals corresponding to shifts from one state to the other and back again -- the researchers could produce histograms resembling the data obtained from experiments on real neurons.

"Supposin, as seems reasonable, that the brain interprets [these characteristic patterns] to obtain information on the frequency and intensity of the stimulus, one comes to the inescapable conclusion that noise plays an essential role in this process," they say.
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Publication:Science News
Date:Aug 31, 1991
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